Pub Date : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9277012
M. Suri, N. Raj, Deepa K, Sarada Jayan
Electric Vehicle (EV) is one of the most preferred vehicles in the current era, as it causes less pollution in the environment when compared to conventional vehicles. The depleted batteries can be refueled using battery charging methods which are further classified as slow, fast and battery swapping methods. EVs wait in queues before they get into service due to long duration of its charging. Queuing theory is used to evaluate behavior of EV charging stations. In this paper, the main objective is to study the different queuing models (M/M) with finite system and infinite system capacity at Fast Charging Stations (FCS). Aspiration level model is used to determine the acceptable range for service. Such models alleviate the difficulty in estimating various costs associated with respect to charging stations. And hence plays a key role in designing battery charging stations in EV developing countries like India. The objective is to understand different queuing models associated with the EV charging station by considering the data of Beijing charging station for a particular private EV.
{"title":"Application of Aspiration Level Model in determining QoS for an EV battery charging station","authors":"M. Suri, N. Raj, Deepa K, Sarada Jayan","doi":"10.1109/ICSTCEE49637.2020.9277012","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9277012","url":null,"abstract":"Electric Vehicle (EV) is one of the most preferred vehicles in the current era, as it causes less pollution in the environment when compared to conventional vehicles. The depleted batteries can be refueled using battery charging methods which are further classified as slow, fast and battery swapping methods. EVs wait in queues before they get into service due to long duration of its charging. Queuing theory is used to evaluate behavior of EV charging stations. In this paper, the main objective is to study the different queuing models (M/M) with finite system and infinite system capacity at Fast Charging Stations (FCS). Aspiration level model is used to determine the acceptable range for service. Such models alleviate the difficulty in estimating various costs associated with respect to charging stations. And hence plays a key role in designing battery charging stations in EV developing countries like India. The objective is to understand different queuing models associated with the EV charging station by considering the data of Beijing charging station for a particular private EV.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125442119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9276929
B. Sunil, Nishanth B. Kulkarni, P. Pradeep, P. K. Praveen, B. Singh, V. Chippalkatti
This paper presents the ultra-low noise and low power LDO regulators for powering the sensor application. The test results show that this LDO output voltage achieves a load regulation of less than 0.1% and ultra-low noise (< 25 nV/root-Hz for frequency > 1 kHz).
{"title":"Design of Low Noise and Low Power LDO for Sensor Application","authors":"B. Sunil, Nishanth B. Kulkarni, P. Pradeep, P. K. Praveen, B. Singh, V. Chippalkatti","doi":"10.1109/ICSTCEE49637.2020.9276929","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9276929","url":null,"abstract":"This paper presents the ultra-low noise and low power LDO regulators for powering the sensor application. The test results show that this LDO output voltage achieves a load regulation of less than 0.1% and ultra-low noise (< 25 nV/root-Hz for frequency > 1 kHz).","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121755458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9276917
G. Preethi, K. Gouthami, Vennela Vajrala, A. Praveena, P. Sireesha
Cognitive Radio (CR) is an intelligent radio that enables the Dynamic Spectrum Access (DSA) against scarcity of available spectrum and inefficient usage of it, by sensing the idle license bands and to use these bands to transmit the data. Two main types of communication technologies used by the Primary User (PU) to be detected by Cognitive Radios are Fixed Frequency (FF) and Frequency Hopping Spread Spectrum (FHSS). In this paper, the design for automatic signal detection i.e. Spectrum Sensing of FF, FH frequencies and classification of FH signal is presented by using the energy detection method. The FH classification is with 25kHz Resolution Bandwidth for 20MHz FH bandwidth. Hardware design is realized in Xilinx System Generator and achieved results for various FF, FH frequencies.
认知无线电(Cognitive Radio, CR)是一种智能无线电，通过感知空闲的许可频带并利用这些频带传输数据，使动态频谱接入(Dynamic Spectrum Access, DSA)能够克服可用频谱稀缺和频谱使用效率低下的问题。认知无线电检测主用户(PU)使用的两种主要通信技术是固定频率(FF)和跳频扩频(FHSS)。本文采用能量检测法对跳频信号进行自动检测，即跳频频率的频谱感知和跳频信号的分类。跳频分类为20MHz跳频带宽的25kHz分辨率带宽。硬件设计在Xilinx System Generator中实现，实现了各种频率的跳频、跳频。
{"title":"Design and Implementation of Non-Cooperative Frequency Detection for Cognitive Radio Application","authors":"G. Preethi, K. Gouthami, Vennela Vajrala, A. Praveena, P. Sireesha","doi":"10.1109/ICSTCEE49637.2020.9276917","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9276917","url":null,"abstract":"Cognitive Radio (CR) is an intelligent radio that enables the Dynamic Spectrum Access (DSA) against scarcity of available spectrum and inefficient usage of it, by sensing the idle license bands and to use these bands to transmit the data. Two main types of communication technologies used by the Primary User (PU) to be detected by Cognitive Radios are Fixed Frequency (FF) and Frequency Hopping Spread Spectrum (FHSS). In this paper, the design for automatic signal detection i.e. Spectrum Sensing of FF, FH frequencies and classification of FH signal is presented by using the energy detection method. The FH classification is with 25kHz Resolution Bandwidth for 20MHz FH bandwidth. Hardware design is realized in Xilinx System Generator and achieved results for various FF, FH frequencies.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133189854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9277402
Anirban Jyoti Hati, Rajiv Ranjan Singh
Plant phenotyping is a smart technique in which plant features data is collected and analyzed using computer vision, robotics and machine learning techniques to increase agricultural production. We propose a leaf segmentation and leaf counting technique based on learning without using the denotation of the leaf center and the data on the plant segmentation given in the LCC CVPPP 2017 dataset. After required segmentation, noise removal and enhancement, as well as the transformation of leaf pixel data, a deep neural network architecture based on Alexnet, was used on a total of 783 plant images by dividing the dataset into 70% for training, 15% for validation and 15% for testing. The result thus obtained showed significant improvement based on four evaluation parameters such as Count Difference, Absolute Count Difference, Percentage of Agreement and Mean Square Error when compared with contemporary works.
{"title":"Towards Smart Agriculture: A Deep Learning based Phenotyping Scheme for Leaf Counting","authors":"Anirban Jyoti Hati, Rajiv Ranjan Singh","doi":"10.1109/ICSTCEE49637.2020.9277402","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9277402","url":null,"abstract":"Plant phenotyping is a smart technique in which plant features data is collected and analyzed using computer vision, robotics and machine learning techniques to increase agricultural production. We propose a leaf segmentation and leaf counting technique based on learning without using the denotation of the leaf center and the data on the plant segmentation given in the LCC CVPPP 2017 dataset. After required segmentation, noise removal and enhancement, as well as the transformation of leaf pixel data, a deep neural network architecture based on Alexnet, was used on a total of 783 plant images by dividing the dataset into 70% for training, 15% for validation and 15% for testing. The result thus obtained showed significant improvement based on four evaluation parameters such as Count Difference, Absolute Count Difference, Percentage of Agreement and Mean Square Error when compared with contemporary works.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133321761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9276892
Ruben John Mampilli, Bharani Ujjaini Kempaiah, K. Goutham, B. Charan
This study aims to examine diagnostic data of patients suffering from the Parkinson’s disease to identify characteristics that are distinctive in the presence of Parkinson’s. The study discovered numerous new correlations such as male Parkinson’s subjects being heavier than their non-Parkinson’s counterparts but indicated no such trend in females. The study also validated previously existing theories including the morphological alterations of the Caudate and Putamen nuclei in the brain as a result of Parkinson’s. Independent datasets obtained from the Parkinson’s Progression Markers Initiative dataset are explored in this study. Furthermore, datasets are created by combining the available data and standard machine learning models are employed to detect the presence of the Parkinson’s disease. A maximum accuracy of 96% was achieved by the Decision Tree model on a merged dataset consisting of medical history, socio-economic background and mobility data.
{"title":"Characterization and detection of Parkinson’s Disease, A data driven approach","authors":"Ruben John Mampilli, Bharani Ujjaini Kempaiah, K. Goutham, B. Charan","doi":"10.1109/ICSTCEE49637.2020.9276892","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9276892","url":null,"abstract":"This study aims to examine diagnostic data of patients suffering from the Parkinson’s disease to identify characteristics that are distinctive in the presence of Parkinson’s. The study discovered numerous new correlations such as male Parkinson’s subjects being heavier than their non-Parkinson’s counterparts but indicated no such trend in females. The study also validated previously existing theories including the morphological alterations of the Caudate and Putamen nuclei in the brain as a result of Parkinson’s. Independent datasets obtained from the Parkinson’s Progression Markers Initiative dataset are explored in this study. Furthermore, datasets are created by combining the available data and standard machine learning models are employed to detect the presence of the Parkinson’s disease. A maximum accuracy of 96% was achieved by the Decision Tree model on a merged dataset consisting of medical history, socio-economic background and mobility data.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134121945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9276971
Jude Abishek Satish, Hussam Taqhi, Harsh Mishra, P. Chetana Reddy, V. Sanju
A Network On Chip (NOC) is a network-based technology that is used for intercommunication of data packets between the various modules present on a System On Chip (SOC). Originally, for this purpose, a simple Bus architecture was used which proved to be very inefficient in terms of latency and throughput. Other topologies like Mesh, 2D Torus, too proved inefficient when compared to the RiCoBiT architecture. This paper reviews the architecture of the novel RiCoBiT topology and assesses it in terms of maximum hop count, average hop count, interfaces, throughput and latency. These simulation results are compared with the previously present architectures like the 2D Mesh, Torus and are found to be more optimal in terms of scalability and efficiency of network communication.
{"title":"RiCoBiT - A topology for the future multi core processor: A concept analysis and review of literature","authors":"Jude Abishek Satish, Hussam Taqhi, Harsh Mishra, P. Chetana Reddy, V. Sanju","doi":"10.1109/ICSTCEE49637.2020.9276971","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9276971","url":null,"abstract":"A Network On Chip (NOC) is a network-based technology that is used for intercommunication of data packets between the various modules present on a System On Chip (SOC). Originally, for this purpose, a simple Bus architecture was used which proved to be very inefficient in terms of latency and throughput. Other topologies like Mesh, 2D Torus, too proved inefficient when compared to the RiCoBiT architecture. This paper reviews the architecture of the novel RiCoBiT topology and assesses it in terms of maximum hop count, average hop count, interfaces, throughput and latency. These simulation results are compared with the previously present architectures like the 2D Mesh, Torus and are found to be more optimal in terms of scalability and efficiency of network communication.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134320783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9277193
M. Quasim, A. Radwan, G. M. M. Alshmrani, M. Meraj
In terms of access, data processing, monitoring and healthcare, the world's health systems experience significant transformations. The advances in data capturing and connected technology are expected to produce about 2314 exabytes of health care data for 2020 [1]. Cyber criminals put a lot of effort for gaining access of healthcare knowledge. This challenge is expected to carry the cybersecurity market to about 27.1 billion dollars in the year 2026 [2]. The blockchain technology will help to form a centralized repository for data collection in clinical experiments. This article suggests a secure system using blockchain to make sure the protection of electronic healthcare records (EHR). The framework includes sensors, Interne of things, databases and other computing resources. This framework for securing EHR will improve the security, privacy of EHR as compared to traditional healthcare system.
{"title":"A Blockchain Framework for Secure Electronic Health Records in Healthcare Industry","authors":"M. Quasim, A. Radwan, G. M. M. Alshmrani, M. Meraj","doi":"10.1109/ICSTCEE49637.2020.9277193","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9277193","url":null,"abstract":"In terms of access, data processing, monitoring and healthcare, the world's health systems experience significant transformations. The advances in data capturing and connected technology are expected to produce about 2314 exabytes of health care data for 2020 [1]. Cyber criminals put a lot of effort for gaining access of healthcare knowledge. This challenge is expected to carry the cybersecurity market to about 27.1 billion dollars in the year 2026 [2]. The blockchain technology will help to form a centralized repository for data collection in clinical experiments. This article suggests a secure system using blockchain to make sure the protection of electronic healthcare records (EHR). The framework includes sensors, Interne of things, databases and other computing resources. This framework for securing EHR will improve the security, privacy of EHR as compared to traditional healthcare system.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116094895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9276856
S. srinivasan, R. Sundar, Sam Joy Herald Immanuel, Ramesh Belvadi, Mithileysh Sathiyanarayanan
In light of the multiple legal issues, compliance and disruptions caused by the pandemic, organisations searching for new solutions need to know what smart contracts are and how they would function under the legal doctrine of force majeure in light of COVID-19. The Blockchains which use Bitcoin type of scripts have been popular as payment solutions, but it is less used as smart contracts. In the case of multi-level games and incremental project payments, there is a high potential to use Bitcoin type of scripts, but it is not being used currently. Interestingly, there have been attempts to associate smart contract mainly using Ethereum Blockchain but not with Bitcoin type of scripts. This article intends to demonstrate the novelty of designing smart contracts using Bitcoin type of scripts for hierarchical execution of smart contracts. An attempt is done to show its application in two use cases (multi-level reward games payment and incremental project payment). An evaluation is done with three methods each having a combination of pros and cons based on the requirements which aids in understanding for transparency and control over funds through Blockchain.
{"title":"Hierarchical Design and Execution of Smart Contracts in Blockchain","authors":"S. srinivasan, R. Sundar, Sam Joy Herald Immanuel, Ramesh Belvadi, Mithileysh Sathiyanarayanan","doi":"10.1109/ICSTCEE49637.2020.9276856","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9276856","url":null,"abstract":"In light of the multiple legal issues, compliance and disruptions caused by the pandemic, organisations searching for new solutions need to know what smart contracts are and how they would function under the legal doctrine of force majeure in light of COVID-19. The Blockchains which use Bitcoin type of scripts have been popular as payment solutions, but it is less used as smart contracts. In the case of multi-level games and incremental project payments, there is a high potential to use Bitcoin type of scripts, but it is not being used currently. Interestingly, there have been attempts to associate smart contract mainly using Ethereum Blockchain but not with Bitcoin type of scripts. This article intends to demonstrate the novelty of designing smart contracts using Bitcoin type of scripts for hierarchical execution of smart contracts. An attempt is done to show its application in two use cases (multi-level reward games payment and incremental project payment). An evaluation is done with three methods each having a combination of pros and cons based on the requirements which aids in understanding for transparency and control over funds through Blockchain.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123252294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9276996
B. Sujatha, B. Vanajakshi, K. Nirmala
First and foremost method of communication between humans is through speech. Speech is the most powerful communication tool if it is used in an appropriate way. These days English has become the most prominent and most used language for interaction between literates. Good communication is possible only if vocabulary of the preferred language is used appropriately. We have found need of a system which analyzes the vocabulary used in the spoken audio which is referred to as speech. This system developed an Integrated Framework for Speech Analysis using Lexical Analyzer (SALA). This system is used in several areas of concern such as in teaching, employment, communication skills, one’s dexterity in English vocabulary. The proposed SALA takes input an audio which consists of English speech. This audio is parallelly recorded and also converted into text and is passed through tokenizer and lexical analyzer, then compared with GSL to create a report of the vocabulary levels used by the speaker in the input audio. This system uses the most popular Speech to Text Conversion to analyze the speech which is a peculiar branch of Artificial Intelligence.
{"title":"SALA-An Integrated Framework for Speech Recognition Using Lexical Analyzer","authors":"B. Sujatha, B. Vanajakshi, K. Nirmala","doi":"10.1109/ICSTCEE49637.2020.9276996","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9276996","url":null,"abstract":"First and foremost method of communication between humans is through speech. Speech is the most powerful communication tool if it is used in an appropriate way. These days English has become the most prominent and most used language for interaction between literates. Good communication is possible only if vocabulary of the preferred language is used appropriately. We have found need of a system which analyzes the vocabulary used in the spoken audio which is referred to as speech. This system developed an Integrated Framework for Speech Analysis using Lexical Analyzer (SALA). This system is used in several areas of concern such as in teaching, employment, communication skills, one’s dexterity in English vocabulary. The proposed SALA takes input an audio which consists of English speech. This audio is parallelly recorded and also converted into text and is passed through tokenizer and lexical analyzer, then compared with GSL to create a report of the vocabulary levels used by the speaker in the input audio. This system uses the most popular Speech to Text Conversion to analyze the speech which is a peculiar branch of Artificial Intelligence.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122684982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9277110
B. Rajan, B. Bhavana, K. Anusha, G. Kusumanjali, G. Pavithra
Hearing loss is often associated with poor performance and incident dementia that leads to reduced social engagements, loneliness, and depression. Hearing aids are a solution for hearing loss. Traditional Hearing aids are an electroacoustic device that blocks noise and enhances target sound out of a multi-source mixture. In some cases when the source objects are devices such as mobiles, laptops, or television a higher distortion happens when the traditional hearing aid amplifies the multi-source mixture which leads the wearer unable to extract the exact information conveyed. This paper proposes a smart internet of things based hearing aid which is cost-effective, reliable, and secured. The smart hearing aid compounds the properties of system on- chip property of micro-controllers which allows the user to connect the internet of things based device directly to the hearing aid, therefore, limiting the multi-source mixture. The micro-controller is equipped with an advance digital signal processor that helps in the separation of acoustic sounds and functions more enhanced compared to the traditional ear aids commercially produced.
{"title":"IoT based Smart and Efficient Hearing Aid using ARM Cortex Microcontroller","authors":"B. Rajan, B. Bhavana, K. Anusha, G. Kusumanjali, G. Pavithra","doi":"10.1109/ICSTCEE49637.2020.9277110","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9277110","url":null,"abstract":"Hearing loss is often associated with poor performance and incident dementia that leads to reduced social engagements, loneliness, and depression. Hearing aids are a solution for hearing loss. Traditional Hearing aids are an electroacoustic device that blocks noise and enhances target sound out of a multi-source mixture. In some cases when the source objects are devices such as mobiles, laptops, or television a higher distortion happens when the traditional hearing aid amplifies the multi-source mixture which leads the wearer unable to extract the exact information conveyed. This paper proposes a smart internet of things based hearing aid which is cost-effective, reliable, and secured. The smart hearing aid compounds the properties of system on- chip property of micro-controllers which allows the user to connect the internet of things based device directly to the hearing aid, therefore, limiting the multi-source mixture. The micro-controller is equipped with an advance digital signal processor that helps in the separation of acoustic sounds and functions more enhanced compared to the traditional ear aids commercially produced.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124342806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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